Engineering Education Factors and Academic Performance in South-Western Nigerian Universities
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Date
2020-06
Journal Title
Journal ISSN
Volume Title
Publisher
World Academics Journal of Engineering Sciences
Abstract
Engineering education has remained the substratum of any society as its contributions towards national development cannot be overemphasized. This is evident in the rapid technological innovations and novel solutions achieved by students with excellent academic performance in universities across the globe. However, some factors have inhibited students’ academic performance in many developing countries especially in the Nigeria experience. These factors are attributed to parental influence, societal pressures, outdated curriculum, lack of state-of-the-art equipment’s and traditional teaching methods. Based on the aforementioned, this paper examined the effect of engineering education factors on academic performance using a survey research design. Primary method of data collection was utilized for administration of 400 copies of questionnaire amongst final year engineering students in the selected tertiary institution in South West, Nigeria. Data were analyzed using multiple regression and artificial neural network analysis. Multiple regression analysis revealed that engineering education factors significantly affects academic performance (R = 0.713, R2 = 0.508, F = 35.105). However, parental influence (p=0.078) and equipment availability (p =0.687) were found not to have significant effect on the students’ academic performance. Artificial neural network analysis further revealed that that lecturers teaching methods has the highest importance (0.437) while equipment’s availability had the least importance (0.050) on the academic performance of the students. It was concluded that engineering educational factors plays a significant role in engendering engineering student performance. The study therefore recommends that an upgrade of the curriculum, innovative teaching methodologies and positive parenting are vital tools for achieving above average learners’ academic performance
Description
Staff Publication
Keywords
Engineering Education,, Academic Performance,, Curriculum,, Teaching Methods,, Artificial Neural Network